Artificial Intelligence Eye Screening System Market Growth Analysis Market 2024-2030

 Market Size and Growth

• In 2023, the global AI Eye Screening System market is estimated to generate a revenue of approximately US$ 126.95 million.
• The market is projected to reach a revenue of US$ 8,978.98 million by 2030, representing a Compound Annual Growth Rate (CAGR) of 82.55% during the period from 2024 to 2030.

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The global Artificial Intelligence (AI) Eye Screening System market is expected to experience significant growth between 2023 and 2030, driven by technological advancements and the increasing demand for efficient and accurate eye screening solutions.

Regional Analysis

• North America and Asia-Pacific have been dominant regions in terms of sales in the past few years.

  
  

  • In 2023, the North America market is expected to hold a 35.09% share of sales, decreasing to 20.15% by 2030.+ In 2023, the Asia-Pacific market is projected to account for 47.98% of sales, increasing to 67.44% by 2030.

• In 2023, the North America market is expected to hold a 35.09% share of sales, decreasing to 20.15% by 2030.+ In 2023, the Asia-Pacific market is projected to account for 47.98% of sales, increasing to 67.44% by 2030.

Product Type and Technology Segmentation

• The AI Eye Screening System market can be segmented based on product type and technology, including Diabetic Retinopathy (DR), Age-Related Macular Degeneration (AMD), Myopia, and Others.

  
  

  • Diabetic Retinopathy (DR) is expected to hold the largest share in 2023 (52.56%) and is projected to increase to 57.88% by 2030.

• Diabetic Retinopathy (DR) is expected to hold the largest share in 2023 (52.56%) and is projected to increase to 57.88% by 2030.

Application Segmentation

• The market can also be segmented based on application, which includes Medical Institutions and Great Health Scene.

  
  

  • Medical Institutions are projected to account for the largest share (61.55%) in 2023, with the share expected to decrease to 53.23% by 2030.

• Medical Institutions are projected to account for the largest share (61.55%) in 2023, with the share expected to decrease to 53.23% by 2030.

Currently, major global companies include Airdoc Technology, Digital Diagnostics, Eyenuk, RetinaLyze System, Optomed, Sibionics Technology, Aeye Health, VUNO, Medimaging Integrated Solution, EyRIS (SELENA+), Vistel and RETINA-AI Health, etc.

This report aims to provide a comprehensive presentation of the global market for Artificial Intelligence Eye Screening System, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Artificial Intelligence Eye Screening System.

The Artificial Intelligence Eye Screening System market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Artificial Intelligence Eye Screening System market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.

For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.

The report will help the Artificial Intelligence Eye Screening System companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.

Market Segmentation

By Company

• Airdoc Technology
• Digital Diagnostics
• Eyenuk
• RetinaLyze System
• Optomed
• Sibionics Technology
• Aeye Health
• VUNO
• Medimaging Integrated Solution
• EyRIS (SELENA+)
• Vistel
• RETINA-AI Health

Segment by Type

• Diabetic Retinopathy (DR)
• Age-Related Macular Degeneration (AMD)
• Myopia
• Others

Segment by Application

• Medical Institutions
• Great Health Scene

By Region

• North America (United States, Canada, Mexico)
• Europe (Germany, France, United Kingdom, Italy, Spain, Rest of Europe)
• Asia-Pacific (China, India, Japan, South Korea, Australia, Rest of APAC)
• The Middle East and Africa (Middle East, Africa)
• South and Central America (Brazil, Argentina, Rest of SCA)

Teleophthalmology and Remote Screening

• The combination of AI-based eye screening systems with telemedicine platforms enables remote diagnosis and monitoring of eye diseases, improving access to eye care services for people in underserved areas.
• AI algorithms can analyze images captured by portable devices or smartphones, facilitating early detection and timely intervention for conditions such as diabetic retinopathy and age-related macular degeneration.

Enhanced Diagnostic Accuracy

• AI systems can analyze vast amounts of data and identify subtle patterns that may be missed by human experts, leading to more accurate and consistent diagnoses.
• Machine learning algorithms can be trained to detect and classify various eye diseases, helping ophthalmologists make better-informed decisions and reducing the risk of misdiagnosis.

Automation and Efficiency

• AI-driven systems can automate repetitive tasks, such as image analysis and grading, allowing ophthalmologists to focus on more complex cases and improving the overall efficiency of eye care services.
• Automated screening can help reduce the backlog of patients waiting for eye exams, leading to shorter wait times and faster initiation of treatment.

Integration with Electronic Health Records (EHRs)

• The integration of AI-based eye screening systems with EHRs can provide a comprehensive view of a patient's medical history, facilitating better decision-making and personalized care.
• This integration can also streamline data management and enable large-scale analysis of clinical data, further improving the accuracy and efficacy of AI algorithms.

Continuous Learning and Improvement

• AI systems can continuously learn and improve as they are exposed to more data, allowing them to adapt to new clinical scenarios and refine their diagnostic capabilities over time.
• This ongoing learning process ensures that AI-based eye screening systems remain up-to-date and effective in the face of evolving disease patterns and clinical practices.

Recent Developments and Announcements in AI Eye Screening Systems

• FDA clearance for Fujifilm's CAD EYE system: Fujifilm received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for its CAD EYE system, an AI-powered endoscopic imaging technology designed to improve the detection of colonic polyps during colonoscopy procedures.

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